Establishment of Transgene‐Free Porcine Induced Pluripotent Stem Cells
Bibliographic record
Abstract
Although protocols to generate authentic transgene-free mouse and human induced pluripotent stem cells (iPSCs) are now well established, standard methods for reprogramming porcine somatic cells still suffer from low efficiency and transgene retention. The Basic Protocol describes reprogramming procedures to establish transgene-free porcine iPSCs (PiPSCs) from porcine fibroblasts. This method uses episomal plasmids encoding POU5F1, SOX2, NANOG, KLF4, SV40LT, c-MYC, LIN28A, and microRNA-302/367, combined with an optimized medium, to establish PiPSC lines. Support protocols describe the establishment and characterization of clonal PiPSC lines, as well as the preparation of feeder cells and EBNA1 mRNA. This optimized, step-by-step approach tailored to this species enables the efficient derivation of PiPSCs in ∼4 weeks. The establishment of transgene-free PiPSCs provides a new and valuable model for studies of larger mammalian species' development, disease, and regenerative biology. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Reprogramming of porcine fibroblasts with episomal plasmids Support Protocol 1: Preparation of mouse embryonic fibroblasts for feeder layer Support Protocol 2: Preparation of in vitro-transcribed EBNA1 mRNA Support Protocol 3: Establishment of clonal porcine induced pluripotent stem cell (PiPSC) lines Support Protocol 4: PiPSC characterization: Genomic DNA PCR and RT-PCR Support Protocol 5: PiPSC characterization: Immunostaining.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".